Energy optimization for single mixed refrigerant natural gas liquefaction process using the metaheuristic vortex search algorithm

Ali, Wahid; Qyyum, Muhammad Abdul; Qadeer, Kinza; Lee, Moonyong

doi:10.1016/j.applthermaleng.2017.10.078

Cited by 51 publications

(29 citation statements)

References 24 publications

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“…In the study, Aspen Hysys is used to model the SMR and C3MR processes. Optimal conditions for the processes as determined by Khan et al [32] are selected to create the base case study. Natural gas feed quality, other process conditions, and assumptions used in the simulation are highlighted in Table 2.…”

Section: Simulation Basis For Lng Process Modelingmentioning

confidence: 99%

“…An exterior penalty function was used to handle the constraints (i.e., MITA value of 3.0 • C), and to further fold the constraints into overall compression power. It has been carried out by several LNG design optimization studies [12,30,32,41].…”

Section: Constraint Handling Approachmentioning

confidence: 99%

“…Recently, a single-solution based Vortex Search (VS) [31] algorithm has been evaluated for the design optimization of complex processes such as modified SMR [32] and self-recuperative high temperature co-electrolysis-based methanol production [33]. Authors have found best optimal designs through the VS approach.…”

Section: Introductionmentioning

confidence: 99%

“…Authors have found best optimal designs through the VS approach. Previously [32], the VS algorithm was used for the design optimization of modifed SMR process (MR consists of five components; nitrogen, methane, ethane, propane, and i-pentane) instead of conventional and well known SMR process that uses four components, i.e., nitrogen, methane, ethane, and propane. Since the optimization of LNG processes exhibited a significant reduction in exergy destruction and an enhanced the energy efficiency.…”

Section: Introductionmentioning

confidence: 99%

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Single-Solution-Based Vortex Search Strategy for Optimal Design of Offshore and Onshore Natural Gas Liquefaction Processes

et al. 2020

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Propane-Precooled Mixed Refrigerant (C3MR) and Single Mixed Refrigerant (SMR) processes are considered as optimal choices for onshore and offshore natural gas liquefaction, respectively. However, from thermodynamics point of view, these processes are still far away from their maximum achievable energy efficiency due to nonoptimal execution of the design variables. Therefore, Liquefied Natural Gas (LNG) production is considered as one of the energy-intensive cryogenic industries. In this context, this study examines a single-solution-based Vortex Search (VS) approach to find the optimal design variables corresponding to minimal energy consumption for LNG processes, i.e., C3MR and SMR. The LNG processes are simulated using Aspen Hysys and then linked with VS algorithm, which is coded in MATLAB. The results indicated that the SMR process is a potential process for offshore sites that can liquefy natural gas with 16.1% less energy consumption compared with the published base case. Whereas, for onshore LNG production, the energy consumption for the C3MR process is reduced up to 27.8% when compared with the previously published base case. The optimal designs of the SMR and C3MR processes are also found via distinctive well-established optimization approaches (i.e., genetic algorithm and particle swarm optimization) and their performance is compared with that of the VS methodology. The authors believe this work will greatly help the process engineers overcome the challenges relating to the energy efficiency of LNG industry, as well as other mixed refrigerant-based cryogenic processes.

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Section: Simulation Basis For Lng Process Modelingmentioning

confidence: 99%

Section: Constraint Handling Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Single-Solution-Based Vortex Search Strategy for Optimal Design of Offshore and Onshore Natural Gas Liquefaction Processes

et al. 2020

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“…, Niu ve Liu Levy uçuşu entegre ederek geliştirdikleri I-VS algoritması ile bir kazanın NOX emisyonlarını tahmin etmişlerdir[22]. Ali, Qyyum, Qadeer ve Lee karışık soğutucu doğal gaz sıvılaştırma işlemi için enerji optimizasyonunda VS algoritmasını kullanmışlardır[23]. Toz, seri robot manipülatörlerin ters kinematik problemini çözmek için VS algoritmasını kullanmıştır[24].…”

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A new model based on vortex search algorithm for estimating energy demand of Turkey

Özkış¹

2020

Pamukkale J Eng Sci

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Bu çalışmada, Türkiye'nin enerji talebini tahmin etmek amacıyla Girdap Arama (Vortex Search, VS) algoritması temelli yeni bir doğrusal regresyon modeli geliştirilmiştir. Modelde Türkiye'deki gayri safi yurtiçi hâsıla (GSYİH), nüfus, ithalat ve ihracat verileri girdi parametrelerini; ortaya çıkan enerji talebi ise tahmin edilecek çıktıyı ifade etmektedir. 1979-2005 ve 1979-2011 yılları arasındaki veriler kullanılarak geliştirilen iki farklı tahmin modeli literatürdeki benzer çalışmalarla karşılaştırılmıştır. Elde edilen sonuçlar, geliştirilen VS modellerinin karşılaştırma yapılan modellerden daha başarılı veya rekabetçi sonuçlar elde ettiğini göstermiştir. Çalışmada son olarak, Türkiye'nin 2030 yılına kadar talep edeceği enerji miktarı, VS ve diğer modeller ile 3 farklı senaryo üzerinden tahmin edilmiştir. In this study, a new linear regression model based on Vortex Search (VS) algorithm was developed for estimating Turkey's energy demand. In this model, Turkey's gross domestic product (GDP), population, import and export data refer to input parameters; resulting energy demand refers to output to be estimated. Two different estimation models developed by using data between 1979-2005 and 1979-2011 were compared with similar studies in the literature. The results showed that the developed VS models obtained more successful or competitive results than the compared models. Finally in this study, the amount of energy that will be demanded in Turkey until 2030 was projected with VS and other models according to 3 different scenarios.

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Weed colonization‐based performance improvement opportunities in dual‐mixed refrigerant natural gas liquefaction process

Qyyum

Qadeer

Khan

et al. 2020

Energy Science & Engineering

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Dual‐mixed refrigerant (DMR) process is a promising candidate for liquefying the natural gas (LNG) at onshore as well as offshore sites, thanks to its higher liquefaction capacity and flexibility in using full gas turbines. DMR involves two mixed refrigerant cycles to perform precooling and subcooling of natural gas (NG), and these refrigerant compositions need constant tweaking to match the ever‐changing NG cooling curve, as it is obtained from different gas fields. Mismatching of cooling curves often results in suboptimal operation, which ultimately leads to an increase in the overall energy consumption. Thus, this study is aimed at making DMR liquefaction operation close to optimal using the invasive‐weed paradigm. At first, the decision variables for performance improvement were determined using degrees of freedom analysis then through invasive‐weed paradigm the best set of parameters that results in minimal overall energy consumption were obtained. For the given set of conditions, it was found that after optimization, the DMR process can produce LNG using 16.2% less compression power compared to the published optimized DMR process. Taking into account the higher sensitivity of the DMR process against NG feed conditions, the IWO approach was also examined to find the multiple optimal solutions corresponding to different sets of feed conditions. The thermodynamic evaluation revealed that the mixed refrigerant involves in NG subcooling and interstage coolers have the highest level of exergy destruction. After successful performance improvement of the DMR process, it is also found that still, 62% improvement potential (based on avoidable/unavoidable exergy destruction analysis) is available in the DMR process that can be attained through either sole optimization or optimal retrofitting/revamping.

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Energy optimization for single mixed refrigerant natural gas liquefaction process using the metaheuristic vortex search algorithm

Cited by 51 publications

References 24 publications

Single-Solution-Based Vortex Search Strategy for Optimal Design of Offshore and Onshore Natural Gas Liquefaction Processes

Single-Solution-Based Vortex Search Strategy for Optimal Design of Offshore and Onshore Natural Gas Liquefaction Processes

A new model based on vortex search algorithm for estimating energy demand of Turkey

Weed colonization‐based performance improvement opportunities in dual‐mixed refrigerant natural gas liquefaction process

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